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PRIMER |生态学数据分析软件

PRIMER | 生态学数据处理软件

 

PRIMER可以帮助研究人员设计最适合引物的应用软件,利用它的高级引物搜索引物数据库巢式引物设计引物编辑和分析等功能可以设计出有高效扩增能力的理想引物也可以设计出用于扩增长达50kb以上的PCR产物的引物序列。

 

PRIMER大量用于生态学数据的处理,它是一套稳健,广泛适用的多变量数据的统计分析包,特别是物种组合,理化变量,基因,微生物,生物指标,饮食,RS,建模等数据。


 PRIMER7的独特特征是能够基于分类的不同或亲缘物种组成计算生物多样性指数。这些例程允许正式的假设测试在一个地点(按物种列表的分类“宽度”的平均和变化),从一个更大的区域物种池中“预期”的变化。它提供了一种可能的方法,当取样工作不受控制时,将生物多样性模式与广泛的空间和时间尺度进行比较。

 

功能特性:

阴影图

显示实际值。可以使用各种标准对示例和变量进行排序,并且可以应用诸如集群之类的约束。

集群

分级聚类到样本(或物种)组。旋转,折叠,缩放图,多页打印输出

MDS和主成分分析

非度量或度量多维尺度(nMDS和mMDS)和主成分(PCA)的顺序。覆盖簇,轨迹,气泡图。

新的- Bootstrap平均值在MDS的图上设置置信区间。额外的MDS覆盖范围如最小生成树。

ANOSIM

总结物种组成和环境变量的模式;基于permut的假设检验(ANOSIM),是单变量方差分析的一个类似物,用于测试不同时间、地点、实验治疗等(多变量)样本组间的差异。

新——现在支持大多数三种方式的设计。

联系

比较(mantel - type)对相似矩阵的测试。

TAXDTEST

分类不同的测试。

其他

标准的多样性指数;摘要统计信息;统治地块也有直方图、方框、线条、条形图;物种丰度分布;阵列的集合,以便在更高的分类学层次上允许数据分析等。

Robust, widely applicable, statistical analysis of multivariate data, e.g. species assemblages, physico-chemical variables, genetic, microbial, biomarker, diet, RS, modelling etc data.

A ‘standard’ for marine community & biodiversity research, increasingly used in terrestrial, freshwater & palaeo studies. Also widely used commercially for assessing environmental impacts of oilfields, discharges, mining, trawling, aquaculture.


The methods make few, if any, assumptions about the form of the data ('non-metric' ordination and permutation tests are fundamental to the approach) and concentrate on approaches that are straightforward to understand and explain.


The statistical methods underlying the software are explained in non-mathematical terms in an extensive 'methods manual', which also shows outcomes from many literature studies, e.g. of environmental effects of oil spills, drilling mud disposal, sewage pollution etc on soft-sediment benthic assemblages, disturbance or climatic effects on coral reef composition or fish communities, more fundamental biodiversity and community ecology patterns, mesocosm studies with multi-species outcomes etc. Many of these full data sets are included with the package so that the user can replicate the analyses given in the manual for himself/herself.


The full integration within a standard Windows environment allows: easy manipulation of data and results, e.g. in input/output from Excel spreadsheets or other sources; the ability to view and manipulate data and some derived files/plots on screen, in multiple windows; standard Windows printing and export to Windows .emf or .bmp files (graphics) and .rtf files (text); flexibility in specifying analyses, particularly for subsets of data and in defining group structures for tests and displays; ability to handle relatively large data sets (subject to available Windows memory and, primarily, time constraints - as with all non-parametric and permutation-based methods, computation time can be long.

 

SHADE PLOT

Display actual values. Samples and variables can be sorted using various criteria, and constraints such as clustering can be applied.

CLUSTER

Hierarchical clustering into sample (or species) groups. Rotate, collapse, zoom plots, multi-page printout

MDS & PCA

Ordination by non-metric or metric multidimensional scaling (nMDS and mMDS) and principal components (PCA). Overlay clusters, trajectories, bubble plots.

NEW - Bootstrap averages puts confidence intervals on an MDS plot. Additional MDS overlays such as minimum spanning trees.

ANOSIM

To summarise patterns in species composition and environmental variables; permutation-based hypothesis testing (ANOSIM), an analogue of univariate ANOVA which tests for differences between groups of (multivariate) samples from different times, locations, experimental treatments etc.

NEW - Now supports most 3 way designs.

SIMPER

Identifies the species primarily providing the discrimination between two observed sample clusters.

BEST

The linking of multivariate biotic patterns to suites of environmental variables. Includes permutation tests.

RELATE

Comparative (Mantel-type) tests on similarity matrices.

TAXDTEST

Taxonomic distinctness tests.

Other

 Standard diversity indices; summary statistics; dominance plots also histogram, box, line, bar plots; species abundance distributions; aggregation of arrays to allow data analysis at higher taxonomic levels, etc.


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